Optimal full-duplex cooperative spectrum sensing in asynchronous cognitive networks

Author(s):  
Teddy Febrianto ◽  
Mohammad Shikh-Bahaei
2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Teddy Febrianto ◽  
Jiancao Hou ◽  
Mohammad Shikh-Bahaei

In asynchronous cognitive networks (CNs), where there is no synchronization between primary users (PUs) and secondary users (SUs), spectrum sensing becomes a challenging task. By combining cooperative spectrum sensing and full-duplex (FD) communications in asynchronous CNs, this paper demonstrates improvements in terms of the average throughput of both PUs and SUs for particular transmission schemes. The average throughputs are derived for SUs and PUs under different FD schemes, levels of residual self-interference, and number of cooperative SUs. In particular, we consider two types of FD schemes, namely, FD transmit-sense-reception (FDr) and FD transmit-sense (FDs). FDr allows SUs to transmit and receive data simultaneously, whereas, in FDs, the SUs continuously sense the channel during the transmission time. This paper shows the respective trade-offs and obtains the optimal scheme based on cooperative FD spectrum sensing. In addition, SUs’ average throughput is analyzed under different primary channel utilization and multichannel sensing schemes. Finally, new FD MAC protocol design is proposed and analyzed for FD cooperative spectrum sensing. We found optimum parameters for our proposed MAC protocol to achieve higher average throughput in certain applications.


Author(s):  
Yunxue Liu ◽  
Dongfeng Yuan ◽  
Mingyan Jiang ◽  
Hui Yu ◽  
Chunyuan Xu ◽  
...  

2017 ◽  
pp. 1-21 ◽  
Author(s):  
Giuseppe Caso ◽  
Mai T. Phuong Le ◽  
Luca De Nardis ◽  
Maria-Gabriella Di Benedetto

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Haibin Jiang ◽  
Zhiyong Yu ◽  
Jian Yang ◽  
Kai Kang

Full-duplex cooperative spectrum sensing (FD-CSS) is an important research field in the field of spectrum sensing. In the FD-CSS network, the secondary user (SU) senses the usage status of the authorized spectrum by the primary user (PU) through the sensing channel and then reports the perceived data to the fusion center (FC) through the reporting channel. The FC makes a comprehensive judgment after summarizing the data through the fusion algorithm. In the secondary network with SU, throughput is an important index to measure the performance of the network. Taking throughput as the optimization goal, this paper theoretically deduces and verifies the optimal data fusion algorithm in cooperative spectrum sensing (CSS), the threshold of optimal energy detection, and the optimal transmission power of SU in the secondary network. The simulation results show the correctness of the results in this paper.


Author(s):  
Mohammad Reza Ghavidel Aghdam ◽  
Reza Abdolee ◽  
S. K. Seyyedi Sahbari ◽  
Behzad Mozaffari Tazehkand

Energy consumption in detection is a key objective for cognitive sensor network. Therefore, measuring the energy consumption is an important issue for efficient spectrum sensing. In order to compute the consumed energy at sensor nodes, their energy probability density function (PDF) is often required. In this article, the authors study the problem of spectrum sensing in cognitive networks and focus on strategies that can substantially affect the energy efficiency and complexity of such algorithms. In particular, they consider an energy detection mechanism in cooperative spectrum sensing where the knowledge of the energy PDF is the key. Since in practice the true value of such a PDF is unavailable, the authors propose to use non-gradient based optimization algorithms to find the parameters of approximated PDF function. In the proposed method, the corresponding PDF parameters are computed iteratively using Genetic and PSO algorithms. The numerical results show that the proposed technique outperforms prior methods.


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